Performance of early warning signals for disease re-emergence: A case study on COVID-19 data

in PLoS Computational Biology (2022), 18(3), 1009958

Developing measures for rapid and early detection of disease re-emergence is important to perform science-based risk assessment of epidemic threats. In the past few years, several early warning signals ... [more ▼]

Developing measures for rapid and early detection of disease re-emergence is important to perform science-based risk assessment of epidemic threats. In the past few years, several early warning signals (EWS) from complex systems theory have been introduced to detect impending critical transitions and extend the set of indicators. However, it is still debated whether they are generically applicable or potentially sensitive to some dynamical charac- teristics such as system noise and rates of approach to critical parameter values. Moreover, testing on empirical data has, so far, been limited. Hence, verifying EWS performance remains a challenge. In this study, we tackle this question by analyzing the performance of common EWS, such as increasing variance and autocorrelation, in detecting the emer- gence of COVID-19 outbreaks in various countries. Our work illustrates that these EWS might be successful in detecting disease emergence when some basic assumptions are sat- isfied: a slow forcing through the transitions and not-fat-tailed noise. In uncertain cases, we observe that noise properties or commensurable time scales may obscure the expected early warning signals. Overall, our results suggest that EWS can be useful for active moni- toring of epidemic dynamics, but that their performance is sensitive to certain features of the underlying dynamics. Our findings thus pave a connection between theoretical and empiri- cal studies, constituting a further step towards the application of EWS indicators for inform- ing public health policies. [less ▲]

COVID-19 Crisis Management in Luxembourg: Insights from an Epidemionomic Approach

in Economics and Human Biology (2021), 43

We develop an epidemionomic model that jointly analyzes the health and economic responses to the COVID-19 crisis and to the related containment and public health policy measures implemented in Luxembourg ... [more ▼]

We develop an epidemionomic model that jointly analyzes the health and economic responses to the COVID-19 crisis and to the related containment and public health policy measures implemented in Luxembourg. The model has been used to produce nowcasts and forecasts at various stages of the crisis. We focus here on two key moments in time, namely the deconfinement period following the first lockdown, and the onset of the second wave. In May 2020, we predicted a high risk of a second wave that was mainly explained by the resumption of social life, low participation in large-scale testing, and reduction in teleworking practices. Simulations conducted 5 months later reveal that managing the second wave with moderately coercive measures has been epidemiologically and economically effective. Assuming a massive third (or fourth) wave will not materialize in 2021, the real GDP loss due to the second wave will be smaller than 0.4 percentage points in 2020 and 2021. [less ▲]

Modelling COVID-19 dynamics and potential for herd immunity by vaccination in Austria, Luxembourg and Sweden

in Journal of Theoretical Biology (2021)

Against the COVID-19 pandemic, non-pharmaceutical interventions have been widely applied and vaccinations have taken off. The upcoming question is how the interplay between vaccinations and social ... [more ▼]

Against the COVID-19 pandemic, non-pharmaceutical interventions have been widely applied and vaccinations have taken off. The upcoming question is how the interplay between vaccinations and social measures will shape infections and hospitalizations. Hence, we extend the Susceptible-Exposed-Infectious-Removed (SEIR) model including these elements. We calibrate it to data of Luxembourg, Austria and Sweden until 15 December 2020. Sweden results having the highest fraction of undetected, Luxembourg of infected and all three being far from herd immunity in December. We quantify the level of social interaction, showing that a level around 1/3 of before the pandemic was still required in December to keep the effective reproduction number Refft below 1, for all three countries. Aiming to vaccinate the whole population within 1 year at constant rate would require on average 1,700 fully vaccinated people/day in Luxembourg, 24,000 in Austria and 28,000 in Sweden, and could lead to herd immunity only by mid summer. Herd immunity might not be reached in 2021 if too slow vaccines rollout speeds are employed. The model thus estimates which vaccination rates are too low to allow reaching herd immunity in 2021, depending on social interactions. Vaccination will considerably, but not immediately, help to curb the infection; thus limiting social interactions remains crucial for the months to come. [less ▲]

Dynamical SPQEIR model assesses the effectiveness of non-pharmaceutical interventions against COVID-19 epidemic outbreaks.

in PloS one (2021), 16(5), 0252019

Against the current COVID-19 pandemic, governments worldwide have devised a variety of non-pharmaceutical interventions to mitigate it. However, it is generally difficult to estimate the joint impact of ... [more ▼]

Against the current COVID-19 pandemic, governments worldwide have devised a variety of non-pharmaceutical interventions to mitigate it. However, it is generally difficult to estimate the joint impact of different control strategies. In this paper, we tackle this question with an extended epidemic SEIR model, informed by a socio-political classification of different interventions. First, we inquire the conceptual effect of mitigation parameters on the infection curve. Then, we illustrate the potential of our model to reproduce and explain empirical data from a number of countries, to perform cross-country comparisons. This gives information on the best synergies of interventions to control epidemic outbreaks while minimising impact on socio-economic needs. For instance, our results suggest that, while rapid and strong lockdown is an effective pandemic mitigation measure, a combination of social distancing and early contact tracing can achieve similar mitigation synergistically, while keeping lower isolation rates. This quantitative understanding can support the establishment of mid- and long-term interventions, to prepare containment strategies against further outbreaks. This paper also provides an online tool that allows researchers and decision makers to interactively simulate diverse scenarios with our model. [less ▲]

Assessing suppression strategies against epidemicoutbreaks like COVID-19: the SPQEIR model

E-print/Working paper (2020)

The current COVID-19 outbreak represents a most serious challenge for societies worldwide. It isendangering the health of millions of people, and resulting in severe socioeconomic challenges dueto lock ... [more ▼]

The current COVID-19 outbreak represents a most serious challenge for societies worldwide. It isendangering the health of millions of people, and resulting in severe socioeconomic challenges dueto lock-down measures. Governments worldwide aim to devise exit strategies to revive the economywhile keeping the pandemic under control. The problem is that the effects of distinct measures arenot well quantified. This paper compares several suppression approaches and potential exit strategiesusing a new extended epidemic SEIR model. It concludes that while rapid and strong lock-down isan effective pandemic suppression measure, a combination of other strategies such as social distanc-ing, active protection and removal can achieve similar suppression synergistically. This quantitativeunderstanding will support the establishment of mid- and long-term interventions. Finally, the paperprovides an online tool that allows researchers and decision makers to interactively simulate diversescenarios with our model. [less ▲]

From Diagnosing Diseases to Predicting Diseases

in Betz, Ulrich A.K. (Ed.) Curious2018 (2019)

Chronic diseases can be considered as perturbations of complex adaptive systems. Transitions from healthy states to chronic diseases are often characterized by sudden and unexpected onset of diseases ... [more ▼]

Chronic diseases can be considered as perturbations of complex adaptive systems. Transitions from healthy states to chronic diseases are often characterized by sudden and unexpected onset of diseases. These critical transitions or catastrophic shifts have been studied in theoretical and applied physics, ecology, social science, economics and recently also in biomedical applications. If we could understand the underlying mechanisms and the dynamics of critical transitions involved in the development of diseases, we would be better equipped to predict and eventually prevent them from arising. The current paper gives an overview of the potential application of the concept of critical transitions to biomedical applications. [less ▲]

Neural Stem Cells of Parkinson's Disease Patients Exhibit Aberrant Mitochondrial Morphology and Functionality

in Stem Cell Reports (2019)

A systems-wide understanding of photosynthetic acclimation in algae and higher plants

in Journal of Experimental Botany (2017), 68(11), 26672681

The ability of phototrophs to colonise different environments relies on robust protection against oxidative stress, a critical requirement for the successful evolutionary transition from water to land ... [more ▼]

The ability of phototrophs to colonise different environments relies on robust protection against oxidative stress, a critical requirement for the successful evolutionary transition from water to land. Photosynthetic organisms have developed numerous strategies to adapt their photosynthetic apparatus to changing light conditions in order to optimise their photosynthetic yield, which is crucial for life on Earth to exist. Photosynthetic acclimation is an excellent example of the complexity of biological systems, where highly diverse processes, ranging from electron excitation over protein protonation to enzymatic processes coupling ion gradients with biosynthetic activity, interact on drastically different timescales from picoseconds to hours. Efficient functioning of the photosynthetic apparatus and its protection is paramount for efficient downstream processes, including metabolism and growth. Modern experimental techniques can be successfully integrated with theoretical and mathematical models to promote our understanding of underlying mechanisms and principles. This review aims to provide a retrospective analysis of multidisciplinary photosynthetic acclimation research carried out by members of the Marie Curie Initial Training Project, AccliPhot, placing the results in a wider context. The review also highlights the applicability of photosynthetic organisms for industry, particularly with regards to the cultivation of microalgae. It intends to demonstrate how theoretical concepts can successfully complement experimental studies broadening our knowledge of common principles in acclimation processes in photosynthetic organisms, as well as in the field of applied microalgal biotechnology. [less ▲]

Making sense of the local Galactic escape speed estimates in direct dark matter searches

in Physical Review. D (2015), 91(2), 023510

Direct detection (DD) of dark matter (DM) candidates in the ≲10 GeV mass range is very sensitive to the tail of their velocity distribution. The important quantity is the maximum weakly interacting ... [more ▼]

Direct detection (DD) of dark matter (DM) candidates in the ≲10 GeV mass range is very sensitive to the tail of their velocity distribution. The important quantity is the maximum weakly interacting massive particle speed in the observer's rest frame, i.e. in average the sum of the local Galactic escape speed v[SUB]esc[/SUB] and of the circular velocity of the Sun v[SUB]c[/SUB]. While the latter has been receiving continuous attention, the former is more difficult to constrain. The RAVE Collaboration has just released a new estimate of v[SUB]esc[/SUB] [T. Piffl et al., Astron. Astrophys. 562, A91 (2014)] that supersedes the previous one [M. C. Smith, et al. Mon. Not. R. Astron. Soc. 379, 755 (2007)], which is of interest in the perspective of reducing the astrophysical uncertainties in DD. Nevertheless, these new estimates cannot be used blindly as they rely on assumptions in the dark halo modeling which induce tight correlations between the escape speed and other local astrophysical parameters. We make a self-consistent study of the implications of the RAVE results on DD assuming isotropic DM velocity distributions, both Maxwellian and ergodic. Taking as references the experimental sensitivities currently achieved by LUX, CRESST-II, and SuperCDMS, we show that (i) the exclusion curves associated with the best-fit points of P14 may be more constraining by up to ˜40 % with respect to standard limits, because the underlying astrophysical correlations induce a larger local DM density, and (ii) the corresponding relative uncertainties inferred in the low weakly interacting massive particle mass region may be moderate, down to 10-15% below 10 GeV. We finally discuss the level of consistency of these results with other independent astrophysical constraints. This analysis is complementary to others based on rotation curves. [less ▲]

Revisiting the escape speed impact on dark matter direct detection

in Proceedings, International Conference: "Frontiers of Fundamental Physics '14", Marseille, France, July 15-18 (2014)

The knowledge of the high velocity tail of the WIMP (Weakly Interacting Massive Particles) velocity distribution has a strong impact on the way dark matter direct detection (DMDD) may constrain or ... [more ▼]

The knowledge of the high velocity tail of the WIMP (Weakly Interacting Massive Particles) velocity distribution has a strong impact on the way dark matter direct detection (DMDD) may constrain or discover light WIMPs in the GeV mass range. Recently, there have been important observational efforts to estimate the Galactic escape speed at the position of the Earth, like for instance the analysis published in early 2014 by the RAVE Collaboration (Piffl et al., 2014), which is of interest in the perspective of reducing the astrophysical uncertainties in DMDD. Nevertheless, these new estimates cannot be used blindly as they rely on assumptions on the Milky Way mass distribution, which induce tight correlations between the escape speed and other local astrophysical parameters (circular speed and dark matter density). We make a self-consistent study of the implications of the RAVE results on DMDD assuming isotropic DM velocity distributions, both Maxwellian and ergodic. Taking as reference the experimental sensitivities currently achieved by LUX, CRESST2, and SuperCDMS, we show that the uncertainties inferred for the exclusion curves in the low WIMP mass region are moderate, ranging from 10% to 20% , and that the RAVE results imply large values of r , and so correspond to exclusion curves that are more constraining than the standard ones by 40%. [less ▲]